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- Title
A Vision-Based Two-Stage Framework for Inferring Physical Properties of the Terrain.
- Authors
Dong, Yunlong; Guo, Wei; Zha, Fusheng; Liu, Yizhou; Chen, Chen; Sun, Lining
- Abstract
The friction and stiffness properties of the terrain are very important pieces of information for mobile robots in motion control, dynamics parameter adjustment, trajectory planning, etc. Inferring the friction and stiffness properties in advance can improve the safety, adaptability and reliability, and reduce the energy consumption of the robot. This paper proposes a vision-based two-stage framework for pre-estimating physical properties of the terrain. We established a field terrain image dataset with weak annotations. A semantic segmentation network that can segment terrains at the pixel level was designed. Given that the same terrain also has different physical properties, we designed two kinds of image features, and we use a decision-making model to realize the mapping from terrain to physical properties. We trained and tested the network comprehensively, and experimented with the complete framework for estimating physical properties. The experimental results show that our framework has good performance.
- Subjects
ROBOT motion; ROBOT control systems; MOBILE robots; TERRAIN mapping; ENERGY consumption; VISION
- Publication
Applied Sciences (2076-3417), 2020, Vol 10, Issue 18, p6473
- ISSN
2076-3417
- Publication type
Article
- DOI
10.3390/app10186473